Student debt planning is one of the most rule-driven planning surfaces in personal finance. Loan type, servicer, IDR plan enrollment, employer status, payment count, recertification timing — every combination produces a different optimal strategy, and the optimal strategy can change overnight when policy moves. The Student Debt Optimization Dataset is 180 households built for the platforms helping borrowers navigate this maze: PSLF candidates, IDR enrollees, Parent PLUS borrowers, refinancing decision-makers, and the tax-bomb-projection cases where forgiveness-event tax owed is a planning factor rather than an afterthought.
Student-debt planning tools have to handle both stability and volatility. The stable parts (loan type taxonomies, IDR plan structures, PSLF qualifying-payment math) are well-defined but structurally complex. The volatile parts (Department of Education servicing transitions, IDR recertification rule changes, IDR account adjustments, executive actions) shift the optimal strategy frequently enough that any tool needs to handle multiple regime states without code changes.
For builders, this means the structural complexity is high. A single household might have direct subsidized and unsubsidized loans, a private refinanced consolidation, Parent PLUS loans for children, and an IDR plan whose qualifying-payment-count just shifted due to the IDR account adjustment. Validating tools against this requires test data with the realistic structural depth — loan-by-loan with servicer, balance, IDR enrollment, and the qualifying-payment count history. Most fixture data is much thinner.
This Data Set provides 180 households where the student-debt structure is fully expressed: every loan as a structured entity with servicer, type, original-disbursement-date, current balance, IDR plan enrollment, qualifying-payment count for PSLF where applicable, refinancing history, and the forgiveness tax-bomb projection.
Validates the platform's PSLF tracker, IDR recertification modeling, and refinancing break-even logic against 180 households whose loan structures span the full taxonomy — direct subsidized/unsubsidized, FFEL pre-2010, Parent PLUS, refinanced consolidations, and the various IDR plan enrollments.
Tests the firm's PSLF certification workflow against employee profiles to surface where the employer-employment-certification process falls short, including the cases where employer-side and employee-side payment-count records diverge.
Validates the firm's forgiveness-tax-bomb projection tools against borrowers whose IDR forgiveness timeline interacts with their projected income trajectory. Surfaces the cases where the forgiveness event itself triggers a meaningful tax obligation that planning should anticipate.
Tests the platform's keep-IDR-vs-refinance decision logic against realistic borrower profiles, ensuring the recommendation correctly accounts for PSLF eligibility, IDR forgiveness timeline, refinancing market rates, and the tax-bomb risk.
Tests the office's debt-counseling tools against realistic graduate-borrower profiles, ensuring the counseling correctly handles the IDR enrollment decision, the Parent PLUS borrower implications, and the forgiveness-eligibility nuances by program.
The 180 households span eleven archetypes covering the student-debt taxonomy: new graduate tech workers (F-01), first-generation wealth builders (F-04), young families with student debt (A-01, A-02), healthcare professionals with high-balance loans (A-05), pre-retirement catch-up cases (P-05), retirees with parent-plus loans (R-01), first-time homebuyers (MB-01), and the niche cases of PSLF candidates (SL-01), IDR enrollees (SL-02), and Parent PLUS borrowers (SL-03).
Every loan in the corpus is structured: servicer (MOHELA, Aidvantage, Nelnet, Edfinancial, etc.), loan type (Direct Subsidized, Direct Unsubsidized, Direct PLUS, Parent PLUS, FFEL Stafford, FFEL Consolidation, Perkins, Private Refinanced), original-disbursement-date, original principal, current balance, current interest rate, IDR enrollment status with the specific plan (SAVE / PAYE / IBR / ICR), qualifying-payment count for PSLF where applicable, and the refinancing history. Forgiveness tax-bomb projections compute the projected forgiveness amount and the projected federal-tax-owed at forgiveness based on the borrower's projected income trajectory. About 30% of the corpus is in active PSLF pursuit; about 25% is in IDR for forgiveness; about 20% is Parent PLUS.
The Data Set ships as JSON and CSV. The WealthSynth Methodology PDF documents the loan-type taxonomy, the IDR plan comparison, the PSLF qualifying-payment-count calculation methodology, the forgiveness-tax-bomb projection framework, and the calibration source for typical borrower profiles by program and life stage.
A redacted summary of one household from this Data Set — names, employers, exact balances, and metro area are stripped. Ages are bucketed, income and net worth are reported as bands. The full record (and all 180 like it) ships in the ZIP.
{
"liabilities.student_loans[]": <value>,
"liabilities.idr_plan_type": <value>,
"benefits.pslf_payments_made": <value>,
"liabilities.refinancing_history": <value>,
"planning.forgiveness_timeline": <value>
}Returns borrowers in PSLF pursuit whose qualifying-payment count is within 24 payments of the 120-payment threshold — the high-leverage outreach window for ensuring certifications are current.
households.filter(h => h.benefits.pslf_payments_made >= 96 && h.benefits.pslf_payments_made < 120 && h.benefits.pslf_employer_eligible )
Returns borrowers whose private-refi rate offer would beat their current weighted-average federal rate by more than 1% AND who don't qualify for PSLF — the candidates where refinancing math meaningfully improves outcomes.
households.filter(h => {
const currentRate = h.liabilities.student_loans
.reduce((s, l) => s + l.balance * l.rate, 0) /
h.liabilities.student_loans
.reduce((s, l) => s + l.balance, 0);
const refiOffer = h.liabilities.refinancing_history?.current_offer_rate;
return refiOffer && currentRate - refiOffer > 0.01 &&
!h.benefits.pslf_employer_eligible;
})Returns borrowers whose IDR forgiveness timeline is within 5 years AND whose projected forgiveness amount exceeds $50K — the tax-planning queue for forgiveness-event tax-savings strategies.
households.filter(h => {
const forgiveYear = h.planning.forgiveness_timeline?.expected_year;
const yearsUntil = forgiveYear - currentYear;
const projectedForgiveness = h.planning.forgiveness_timeline
?.projected_balance_at_forgiveness;
return yearsUntil > 0 && yearsUntil <= 5 &&
projectedForgiveness > 50000;
})Returns borrowers whose IDR recertification deadline is within 90 days — the queue for outreach to ensure recertification is completed before the deadline triggers a payment-recalculation event.
households.filter(h =>
h.liabilities.student_loans
.some(l => l.idr_plan_type !== null) &&
h.liabilities.idr_recertification_deadline &&
daysBetween(today(), h.liabilities.idr_recertification_deadline) <= 90
)Each household's student-debt profile is generated against archetype-specific patterns. New-graduate tech workers carry typical undergraduate-only loan profiles ($30K-$70K total balance). Healthcare professionals carry high-balance graduate-school loan profiles ($150K-$400K total). PSLF candidates concentrate in nonprofit-employed and government-employed archetypes. Parent PLUS borrowers are typically pre-retiree households with adult children. IDR plan enrollment uses realistic distributions calibrated against Department of Education published statistics (SAVE plan dominant for new enrollees; older borrowers more concentrated in IBR or PAYE). PSLF qualifying-payment counts use the IDR Account Adjustment retroactive adjustments where applicable. Refinancing history uses realistic break-even calculations against current private-refi market rates. Forgiveness tax-bomb projections compute the projected forgiveness balance and the projected federal-tax-owed at forgiveness using the borrower's projected income trajectory. The corpus passes the WealthSynth consistency validator (loan balances reconcile with payment history; IDR plan enrollment is consistent with eligibility; PSLF payment counts are mathematically consistent) and the LLM-as-judge gate. Annual refresh tracks Department of Education policy changes, IDR rule updates, and PSLF interpretive guidance.
The corpus tracks current Department of Education rules including the SAVE plan structure, the IDR account adjustment retroactive credit, and the post-2023 PSLF processing improvements. Annual refresh tracks subsequent rule changes — student-loan policy moves frequently and the bundle is calibrated for the current state.
Yes. The corpus reflects current servicer assignments (MOHELA for PSLF, Aidvantage, Nelnet, Edfinancial). Borrowers whose loans transitioned servicers in the past 24 months have the structured transition history with any payment-count discrepancies surfaced — these discrepancies are the most common cause of PSLF certification disputes.
Yes. About 18% of the corpus carries Parent PLUS debt — typically pre-retiree parents who took loans for adult children's education. The structured Parent PLUS data includes the Double Consolidation Loophole pathway where applicable (a planning structure that converts Parent PLUS loans to ICR-eligible status).
Yes. Borrowers who refinanced federal loans into private consolidations have structured refinancing-history data showing the federal-loan-loss (PSLF eligibility lost, IDR access lost) and the rate savings achieved. The structured data lets your tools surface the trade-off correctly.
Yes. IDR forgiveness is currently taxable as ordinary income at forgiveness (with the temporary federal exclusion through 2025 — a structural fact the corpus tracks). The projection methodology accounts for the borrower's projected income at forgiveness, the projected forgiveness balance based on IDR payment trajectory, and the federal-marginal-rate calculation. State-level tax treatment varies and is documented per-state.
Yes. About 12% of the corpus has at least one FFEL loan. The structured FFEL data captures the ineligibility for direct PSLF (without consolidation) and the structural challenges these borrowers face. The Department's recent FFEL Consolidation guidance is reflected.
Yes. Borrowers with multiple loans of different types have structured consolidation-eligibility analysis: which combinations make sense for PSLF pursuit, which combinations help with IDR, where consolidation forgoes important features (Perkins cancellation, FFEL flexibility). The recommendation is structured for advisor display.
B19 focuses specifically on student debt — PSLF, IDR, refinancing, forgiveness tax bomb. B23 focuses on broader inclusive-lending product design (alternative data underwriting, second-chance loans, ITIN mortgage). They overlap at the underserved-borrower seam — first-generation wealth builders often have student debt as their primary planning challenge. Many lending-focused buyers purchase both.
400 prospect households covering RIA client variety from formation through retirement. KYC-complete records, goal-based planning fields, initial recommendation outputs, and CRM-compatible field naming. The broadest single bundle by archetype coverage.
90 active-duty, retired, and veteran households spanning enlisted to officer ranks. BRS pension elections, TSP allocations, VA loan entitlements, BAH/BAS allowances, SBP elections, VA disability compensation, CRDP/CRSC, and PSLF for nonprofit-employed veterans.
100 households underserved by traditional financial services: thin-credit-file ITIN filers, post-bankruptcy rebuilders, low-income working families, recent immigrants, disability claimants, and cannabis-industry workers. Useful for CRA-aligned lending and inclusion analytics.
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